Modern AI depends on trustworthy data, but many organizations still rely on decades-old databases filled with undocumented relationships, duplicate records, and inconsistent business rules.

Drawing from a real-world government modernization project, this session walks through the complete migration journey—from reverse engineering legacy SQL databases to building reliable cloud-ready data platforms.

We'll discuss schema reconstruction, business rule discovery, staging strategies, validation frameworks, reconciliation techniques, and production cutover planning. You'll also learn how these engineering practices create the foundation for future AI initiatives.

Whether you're modernizing legacy applications or preparing data for analytics and AI, this session offers practical techniques you can apply immediately.

What you'll learn
Reverse engineering legacy databases
Designing migration pipelines
Data validation strategies
Production cutover planning
Preparing SQL environments for AI